Semantics-Aware Virtual Machine Image Management in IaaS Clouds

Abstract

Infrastructure-as-a-service (IaaS) Clouds concurrently accommodate diverse sets of user requests, requiring an efficient strategy for storing and retrieving virtual machine images (VMIs) at a large scale. The VMI storage management require dealing with multiple VMIs, typically in the magnitude of gigabytes, which entails VMI sprawl issues hindering the elastic resource management and provisioning. Nevertheless, existing techniques to facilitate VMI management overlook VMI semantics (i.e at the level of base image and software packages) with either restricted possibility to identify and extract reusable functionalities or with higher VMI publish and retrieval overheads. In this paper, we design, implement and evaluate Expelliarmus, a novel VMI management system that helps to minimize storage, publish and retrieval overheads. To achieve this goal, Expelliarmus incorporates three complementary features. First, it makes use of VMIs modelled as semantic graphs to expedite the similarity computation between multiple VMIs. Second, Expelliarmus provides a semantic aware VMI decomposition and base image selection to extract and store non-redundant base image and software packages. Third, Expelliarmus can also assemble VMIs based on the required software packages upon user request. We evaluate Expelliarmus through a representative set of synthetic Cloud VMIs on the real test-bed. Experimental results show that our semantic-centric approach is able to optimize repository size by 2.2 − 16 times compared to state-ofthe-art systems (e.g. IBM's Mirage and Hemera) with significant VMI publish and retrieval performance improvement.

Efficiency in the serverless cloud paradigm: A survey on the reusing and approximation aspects

“…Although deduplicating redundant layers is already widely used by the runtimes, further research works have recently been undertaken to improve the efficiency of deduplicating 99,100 and to extend the deduplication idea to reuse similar layers. 121 Notably, Zhao et al Duphunter 99 is a replacement layer loading module for the Docker platform. The architecture is more effective in deduplicating similar layers across multiple docker images with less deduplication overhead than prior designs.…”

“…Then, they only differ on the application and model layers. Although deduplicating redundant layers is already widely used by the runtimes, further research works have recently been undertaken to improve the efficiency of deduplicating 99,100 and to extend the deduplication idea to reuse similar layers 121 . Notably, Zhao et al Duphunter 99 is a replacement layer loading module for the Docker platform.…”

Efficiency in the Serverless Cloud Computing Paradigm: A Survey Study

“…Then they only differ on the application and model layers. Although deduplicating redundant layers is already widely-used by the runtimes, further research works have recently been undertaken to improve the efficiency of deduplicating [90], [91] and to extend the deduplication idea to reuse similar layers [92]. Notably, Zhao et al, 's Duphunter [90] is a replacement layer loading module for Docker platform.…”